Machine Learning For Cybersecurity Threat Detection And Mitigation
DOWNLOAD
Download Machine Learning For Cybersecurity Threat Detection And Mitigation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning For Cybersecurity Threat Detection And Mitigation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Machine Learning For Cybersecurity Threat Detection And Mitigation
DOWNLOAD
Author : Dr. Araddhana Arvind Deshmukh
language : en
Publisher: Xoffencer international book publication house
Release Date : 2024-07-05
Machine Learning For Cybersecurity Threat Detection And Mitigation written by Dr. Araddhana Arvind Deshmukh and has been published by Xoffencer international book publication house this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-05 with Computers categories.
As a result of the increasingly complex structure of today's information systems, there is a growing agreement that Artificial Intelligence (AI) is required in order to keep up with the exponential expansion of big data. Techniques from the field of machine learning (ML), in particular deep learning, are already being used to address a broad range of issues that are encountered in the real world. There are a number of intriguing examples of machine learning's practical triumphs, including machine translation, recommendations for vacations and travel, item identification and monitoring, and even various applications in the healthcare industry. Furthermore, machine learning has shown a great deal of promise in the area of autonomous driving and communication systems, which is why it is rightly considered to be a technical enabler. On the other hand, the civilization of today is more reliant than ever before on information technology systems, even autonomous ones, which are itself abused by malicious actors. In actuality, cybercriminals are always inventing new threats, and, they will have the ability to do significant harm or even kill people due to their capabilities. In order for defensive mechanisms to be able to prevent such events and limit the multiplicity of hazards that might potentially harm both current and future information technology systems, they need to be able to quickly adapt to (i) settings that are continually changing and (ii) threat landscapes that are always developing. It is hard to ignore the use of machine learning in the field of cybersecurity since it is manifestly impossible to address such a dual demand using methodologies that are static and human-defined. It is not surprising that a number of surveys and technical studies have been conducted on the subject of machine learning integration in the field of cybersecurity. Even though there have been a lot of accomplishments in research settings, there has been only a little amount of progress made in creating and integrating machine learning in industrial systems. The vast majority of these solutions are still using 'unsupervised' techniques, mostly for 'anomaly detection,' according to a recent report. This is despite the fact that more than ninety percent of enterprises are presently incorporating AI and ML into their defensive systems.
Machine Learning For Cybersecurity
DOWNLOAD
Author : Abdussalam Elhanashi
language : en
Publisher:
Release Date : 2024-12-12
Machine Learning For Cybersecurity written by Abdussalam Elhanashi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Mathematics categories.
"Machine Learning for Cybersecurity: Threat Detection and Mitigation" delves into the transformative role of machine learning in addressing contemporary cybersecurity challenges. This reprint provides an in-depth exploration of how advanced techniques such as deep learning, natural language processing, and explainable AI are revolutionizing intrusion detection, anomaly detection, and threat intelligence. With a focus on practical applications, it covers critical topics such as malware analysis, IoT and cloud security, blockchain security, adversarial attacks, and secure data sharing. Through this reprint, readers will gain insights into cutting-edge approaches for vulnerability assessments, authentication, and privacy preservation while exploring frameworks for implementing security-aware AI systems. This comprehensive resource is essential for researchers, practitioners, and policymakers striving to strengthen digital ecosystems. It offers both theoretical insights and actionable solutions, paving the way for innovative cybersecurity strategies to combat an ever-evolving threat landscape.
Ai Driven Cybersecurity And Threat Intelligence
DOWNLOAD
Author : Iqbal H. Sarker
language : en
Publisher: Springer Nature
Release Date : 2024-04-28
Ai Driven Cybersecurity And Threat Intelligence written by Iqbal H. Sarker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-28 with Computers categories.
This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world. Overall, the useof AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book.
Machine Intelligence Applications In Cyber Risk Management
DOWNLOAD
Author : Almaiah, Mohammed Amin
language : en
Publisher: IGI Global
Release Date : 2024-11-29
Machine Intelligence Applications In Cyber Risk Management written by Almaiah, Mohammed Amin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.
In an era where cyber threats are increasingly sophisticated and persistent, the intersection of machine intelligence and cyber-risk management represents a pivotal frontier in the defense against malicious actors. The rapid advancements of artificial intelligence (AI) and machine learning (ML) technologies offer unprecedented capabilities for identifying, analyzing, and mitigating cyber risks. These technologies not only improve the speed and accuracy of identifying potential threats but also enable proactive and adaptive security measures. Machine Intelligence Applications in Cyber-Risk Management explores the diverse applications of machine intelligence in cyber-risk management, providing a comprehensive overview of how AI and ML algorithms are utilized for automated incident response, threat intelligence gathering, and dynamic security postures. It addresses the pressing need for innovative solutions to combat cyber threats and offer insights into the future of cybersecurity, where machine intelligence plays a crucial role in creating resilient and adaptive defense mechanisms. Covering topics such as anomy detection algorithms, malware detection, and wireless sensor networks (WSNs), this book is an excellent resource for cybersecurity professionals, researchers, academicians, security analysts, threat intelligence experts, IT managers, and more.
The Next Frontier In Cybersecurity Integrating Ai Ml And Generative Ai For Advanced Protection
DOWNLOAD
Author : Dr Sivaraju Kuraku
language : en
Publisher: JEC PUBLICATION
Release Date :
The Next Frontier In Cybersecurity Integrating Ai Ml And Generative Ai For Advanced Protection written by Dr Sivaraju Kuraku and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Architecture categories.
......
Ml And Cybersecurity Ai For Threat Detection And Prevention
DOWNLOAD
Author : Dr. Araddhana Manisha Arvind Deshmukh
language : en
Publisher: Academic Guru Publishing House
Release Date : 2025-01-06
Ml And Cybersecurity Ai For Threat Detection And Prevention written by Dr. Araddhana Manisha Arvind Deshmukh and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Study Aids categories.
ML and Cybersecurity: Al for Threat Detection and Prevention" is a comprehensive guide that focuses on the critical role of Artificial Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. As cyber threats become increasingly sophisticated and frequent, traditional security methods struggle to provide adequate protection. This book addresses the growing demand for Al-powered solutions that can detect and prevent threats in real-time. The book provides a detailed exploration of various Al and ML techniques used to enhance cybersecurity, including supervised and unsupervised learning, behavioral analysis, and predictive analytics. It explains how Al technologies help identify threats faster and more accurately, reduce human error, and streamline security processes. Moreover, the book highlights practical applications and real-world examples, including Al-powered intrusion detection systems, automated incident response, and enhanced security information systems. Additionally, ethical considerations, privacy concerns, and challenges related to integrating Al with cybersecurity are thoroughly examined.
Predicting The Unknown Machine Learning For Zero Day Vulnerability Detection A Data Driven Approach To Securing The Future
DOWNLOAD
Author : Hariprasad Sivaraman
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2022-07-15
Predicting The Unknown Machine Learning For Zero Day Vulnerability Detection A Data Driven Approach To Securing The Future written by Hariprasad Sivaraman and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-15 with Computers categories.
Zero-day vulnerabilities pose one of the most pressing cybersecurity threats, allowing attackers to exploit software flaws before security teams can respond. Predicting the Unknown: Machine Learning for Zero- Day Vulnerability Detection presents a cutting-edge approach to combating these threats using AI-driven techniques, empowering security professionals with proactive defense strategies. This book explores the limitations of traditional security models—such as signature-based and heuristic detection—and highlights how machine learning (ML) is transforming zero-day threat detection. Readers will discover how ML models, including anomaly detection, supervised and unsupervised learning, and reinforcement learning, can analyze vast datasets of network traffic and system logs to identify emerging vulnerabilities before they are exploited. From feature engineering and real-time anomaly detection to adversarial machine learning and evasion tactics, Predicting the Unknown delves into the core components of AI-powered cybersecurity. The book also examines advanced ML techniques like deep learning and reinforcement learning, showcasing their role in dynamic threat mitigation. Packed with case studies, technical insights, and future trends—including the integration of quantum computing and explainable AI—this book provides a comprehensive roadmap for security professionals, data scientists, and researchers. Whether you're looking to strengthen enterprise defenses or pioneer nextgeneration cybersecurity solutions, Predicting the Unknown equips you with the tools to stay ahead of evolving cyber threats.
Protecting And Mitigating Against Cyber Threats
DOWNLOAD
Author : Sachi Nandan Mohanty
language : en
Publisher: John Wiley & Sons
Release Date : 2025-07-29
Protecting And Mitigating Against Cyber Threats written by Sachi Nandan Mohanty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-29 with Computers categories.
The book provides invaluable insights into the transformative role of AI and ML in security, offering essential strategies and real-world applications to effectively navigate the complex landscape of today’s cyber threats. Protecting and Mitigating Against Cyber Threats delves into the dynamic junction of artificial intelligence (AI) and machine learning (ML) within the domain of security solicitations. Through an exploration of the revolutionary possibilities of AI and ML technologies, this book seeks to disentangle the intricacies of today’s security concerns. There is a fundamental shift in the security soliciting landscape, driven by the extraordinary expansion of data and the constant evolution of cyber threat complexity. This shift calls for a novel strategy, and AI and ML show great promise for strengthening digital defenses. This volume offers a thorough examination, breaking down the concepts and real-world uses of this cutting-edge technology by integrating knowledge from cybersecurity, computer science, and related topics. It bridges the gap between theory and application by looking at real-world case studies and providing useful examples. Protecting and Mitigating Against Cyber Threats provides a roadmap for navigating the changing threat landscape by explaining the current state of AI and ML in security solicitations and projecting forthcoming developments, bringing readers through the unexplored realms of AI and ML applications in protecting digital ecosystems, as the need for efficient security solutions grows. It is a pertinent addition to the multi-disciplinary discussion influencing cybersecurity and digital resilience in the future. Readers will find in this book: Provides comprehensive coverage on various aspects of security solicitations, ranging from theoretical foundations to practical applications; Includes real-world case studies and examples to illustrate how AI and machine learning technologies are currently utilized in security solicitations; Explores and discusses emerging trends at the intersection of AI, machine learning, and security solicitations, including topics like threat detection, fraud prevention, risk analysis, and more; Highlights the growing importance of AI and machine learning in security contexts and discusses the demand for knowledge in this area. Audience Cybersecurity professionals, researchers, academics, industry professionals, technology enthusiasts, policymakers, and strategists interested in the dynamic intersection of artificial intelligence (AI), machine learning (ML), and cybersecurity.
Deep Learning Innovations For Securing Critical Infrastructures
DOWNLOAD
Author : Kumar, Rajeev
language : en
Publisher: IGI Global
Release Date : 2025-04-18
Deep Learning Innovations For Securing Critical Infrastructures written by Kumar, Rajeev and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-18 with Computers categories.
Deep learning innovations play a crucial role in securing critical infrastructures, offering advanced solutions to protect vital systems from sophisticated cyber threats. By leveraging neural networks and advanced algorithms, deep learning enables real-time anomaly detection, pattern recognition, and predictive threat analysis, which are essential for safeguarding critical sectors such as energy, transportation, healthcare, and finance. These technologies can identify vulnerabilities, respond to breaches, and adapt to new attacks, providing a strong defense against cyber risks. As the digital landscape becomes more interconnected, the integration of deep learning into cybersecurity strategies will enhance resilience while ensuring the safe operation of essential services. Deep Learning Innovations for Securing Critical Infrastructures explores the cutting-edge integration of neural networks and artificial intelligence (AI) in modern cybersecurity systems. It examines how AI, particularly neural network models, is revolutionizing cybersecurity by automating threat detection, analyzing complex data patterns, and implementing proactive defense mechanisms. This book covers topics such as blockchain, cloud computing, and event management, and is a useful resource for business owners, computer engineers, data scientists, academicians, and researchers.
The Intersection Of Ai And Cybersecurity Building Smarter Defense Systems
DOWNLOAD
Author : Muhammad Ismaeel khan
language : en
Publisher: JEC PUBLICATION
Release Date :
The Intersection Of Ai And Cybersecurity Building Smarter Defense Systems written by Muhammad Ismaeel khan and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
.